Eliciting the child's voice in adverse event reporting in oncology trials: Cognitive interview findings from the Pediatric Patient‐Reported Outcomes version of the Common Terminology Criteria for Adverse Events initiative
Bibliographic record
Abstract
BACKGROUND: Adverse event (AE) reporting in oncology trials is required, but current practice does not directly integrate the child's voice. The Pediatric Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) is being developed to assess symptomatic AEs via child/adolescent self-report or proxy-report. This qualitative study evaluates the child's/adolescent's understanding and ability to provide valid responses to the PRO-CTCAE to inform questionnaire refinements and confirm content validity. PROCEDURE: From seven pediatric research hospitals, children/adolescents ages 7-15 years who were diagnosed with cancer and receiving treatment were eligible, along with their parent-proxies. The Pediatric PRO-CTCAE includes 130 questions that assess 62 symptomatic AEs capturing symptom frequency, severity, interference, or presence. Cognitive interviews with retrospective probing were completed with children in the age groups of 7-8, 9-12, and 13-15 years. The children/adolescents and proxies were interviewed independently. RESULTS: Two rounds of interviews involved 81 children and adolescents and 74 parent-proxies. Fifteen of the 62 AE terms were revised after Round 1, including refinements to the questions assessing symptom severity. Most participants rated the PRO-CTCAE AE items as "very easy" or "somewhat easy" and were able to read, understand, and provide valid responses to questions. A few AE items assessing rare events were challenging to understand. CONCLUSIONS: The Pediatric and Proxy PRO-CTCAE performed well among children and adolescents and their proxies, supporting its content validity. Data from PRO-CTCAE may improve symptomatic AE reporting in clinical trials and enhance the quality of care that children receive.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".